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Assessing the Codetermination of Gene Transcriptional States Using Both Superscalar and Vector Multiple Processor Systems

Authors: R, Martino; D E, Russ; C A, Johnson;

Assessing the Codetermination of Gene Transcriptional States Using Both Superscalar and Vector Multiple Processor Systems

Abstract

An important goal of functional genomics is to develop methods for determining ways in which individual actions of genes are integrated in the cell. One way of gaining insight into a gene's role in cellular activity is to study its expression pattern in a variety of circumstances and contexts, as it responds to its environment and to the action of other genes. Microarrays provide large-scale surveys of gene expression in which transcript levels can be determined for thousands of genes simultaneously. The coefficient of determination (CoD) has been proposed for the analysis of gene interaction via multivariate expression arrays. Parallel computing is essential to the application of the CoD to a large set of genes because of the large number of expression-based functions that must be statistically designed and compared. The results of the calculation of the CoD for a large set of genes with multiple superscalar processors are presented. A proposal for calculating the CoD with multiple vector processors is described. Multiple vector processor systems offer the potential to greatly reduce the time to calculate the CoD for a large set of genes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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